Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification

Embedding cost-sensitive factors into the classifiers increases the classification stability and reduces the classification costs for classifying high-scale, redundant, and imbalanced datasets, such as the gene expression data. In this study, we extend our previous work, that is, Dissimilar ELM (D-E...

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Vydáno v:Comput Intell Neurosci
Hlavní autoři: Liu, Yanqiu, Lu, Huijuan, Yan, Ke, Xia, Haixia, An, Chunlin
Médium: Artigo
Jazyk:Inglês
Vydáno: Hindawi Publishing Corporation 2016
Témata:
Research Article
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5011754/
https://ncbi.nlm.nih.gov/pubmed/27642292
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/8056253
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